Vehicle Radar Perception And Localization

ABSTRACT

The disclosure relates to methods, systems, and apparatuses for autonomous driving vehicles or driving assistance systems and more particularly relates to vehicle radar perception and location. The vehicle driving system disclosed may include a storage media, a radar system, a location component and a driver controller. The storage media stores a map of roadways. The radar system is configured to generate perception information from a region near the vehicle. The location component is configured to determine a location of the vehicle on the map based on the radar perception information and other navigation related data. The drive controller is configured to control driving of the vehicle based on the map and the determined location.

CROSS REFERENCE TO RELATED PATENT APPLICATION

This application is a continuation of and claims the benefit of andpriority to U.S. patent application Ser. No. 16/052,122, filed Aug. 1,2018, which is a continuation of and claims the benefit of and priorityto U.S. patent application Ser. No. 14/856,010, filed Sep. 16, 2015, theentire contents of which are expressly incorporated by references.

TECHNICAL FIELD

The disclosure relates generally to methods, systems, and apparatusesfor autonomous driving vehicles or driving assistance systems and moreparticularly relates to vehicle radar perception and location.

BACKGROUND

Autonomous vehicles and driving assistance systems are currently beingdeveloped and deployed to provide safety, reduce an amount of user inputrequired, or even eliminate user involvement entirely. For example, somedriving assistance systems, such as crash avoidance systems, may monitordriving, positions, and velocities of the vehicle and other objectswhile a human is driving. When the system detects that a crash or impactis imminent the crash avoidance system may intervene and apply a brake,steer the vehicle, or perform other avoidance or safety maneuvers. Asanother example, autonomous vehicles may drive and navigate a vehiclewith little or no user input. However, due to the dangers involved indriving and the costs of vehicles, it is extremely important thatautonomous vehicles and driving assistance systems operate safely andare able to accurately navigate roads, avoid objects, and observe theirsurroundings. Furthermore, current autonomous vehicles and drivingassistance systems may struggle to operate safely or correctly due tothe wide variety of terrain, weather conditions, and other environmentsin which vehicles often operate. Thus, autonomous vehicles must operatesafely under adverse conditions and perceive the environment asaccurately as possible, even if some of the vehicle's sensors fail.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive implementations of the presentdisclosure are described with reference to the following figures,wherein like reference numerals refer to like parts throughout thevarious views unless otherwise specified. Advantages of the presentdisclosure will become better understood with regard to the followingdescription and accompanying drawings where:

FIG. 1 is a schematic block diagram illustrating an implementation of avehicle that includes an automated driving/assistance system;

FIG. 2 is a schematic top view diagram illustrating a roadway, accordingto one embodiment;

FIG. 3 is a schematic block diagram illustrating example components of alocalization component, according to one implementation; and

FIG. 4 is a schematic flow chart diagram illustrating a method forperception and localization for a road vehicle, according to oneimplementation.

DETAILED DESCRIPTION

Under driving conditions such as a snow-covered roads without buildingsor other landmarks, cameras and light detection and ranging (LIDAR)systems have difficulty due to the low visual contrast and highreflectivity of the environment. Weather conditions, including dense fogand rain, can severely limit camera and LIDAR data acquisition.Additionally, the reflectivity of widespread water on the ground can bechallenging for both LIDAR and visual systems. Under thesecircumstances, applicants have recognized that the most reliable dataavailable includes data from radio detection and ranging (radar),positioning systems such as a global positioning systems (GPS), digitalmaps such as high definition (HD) maps, drive history, andvehicle-to-vehicle (V2V) and vehicle to infrastructure (V2X)communication.

Even if a driver assist feature or autonomous driving solutions makesuse of various combinations of sensors (such as LIDAR), camera(s), andmaps in the vehicle's memory, these features or solutions may be unableto provide useful information due to environmental conditions or damage.Radar will frequently be able to provide useful information even inthese conditions. Thus, some embodiments herein combine any availableradar data with as much other information that the vehicle can obtainabout its environment as possible, including not only HD maps, but alsodrive history and V2X communication, for example.

The present disclosure discusses systems, methods, and devices forintegrating data from radar sensors on a vehicle with data from othersources of information such as GPS, HD maps, and drive historyinformation, to more completely and accurately localize a vehicle on aroad and perceive relevant parts of the environment, such as obstacles.Information from vehicle-to-vehicle or vehicle-to-infrastructure (V2X)communication may also be taken into account by these perception andlocalization algorithms. Some embodiments include performing perceptionand localization for use with autonomous navigation and active safety ordriver assist features. In one embodiment, information from previousdrives is stored in the vehicle's memory, including route geometry andbehavioral features from previous trips along the same path. In oneembodiment, HD maps in the vehicle's memory detail information about thepositions of roads, lane markings, traffic signs, or other locations interms of GPS coordinates. In one embodiment, other vehicles and the roadinfrastructure wirelessly share information from their own sensors tosupplement the vehicle's on board perception. In one embodiment,information from the vehicle's on-board GPS, in combination withreadings from its radar sensors and any information gained via V2V orV2X communication, is used to determine a location of the vehicle(localize the vehicle) on the HD map and relative to any drive historydata. In one embodiment, the vehicle may navigate or maneuverautonomously based on the determined location(s), provided sufficientconfidence in its perception of its surroundings can be achieved. Apotential advantage of using a radar system to provide perceptioninformation for a vehicle is that useful data can be acquired in evenvery adverse weather conditions.

In the following disclosure, reference is made to the accompanyingdrawings, which form a part hereof, and in which is shown by way ofillustration specific implementations in which the disclosure may bepracticed. It is understood that other implementations may be utilizedand structural changes may be made without departing from the scope ofthe present disclosure. References in the specification to “oneembodiment,” “an embodiment,” “an example embodiment,” etc., indicatethat the embodiment described may include a particular feature,structure, or characteristic, but every embodiment may not necessarilyinclude the particular feature, structure, or characteristic. Moreover,such phrases are not necessarily referring to the same embodiment.Further, when a particular feature, structure, or characteristic isdescribed in connection with an embodiment, it is submitted that it iswithin the knowledge of one skilled in the art to affect such feature,structure, or characteristic in connection with other embodimentswhether or not explicitly described.

Implementations of the systems, devices, and methods disclosed hereinmay comprise or utilize a special purpose or general-purpose computerincluding computer hardware, such as, for example, one or moreprocessors and system memory, as discussed in greater detail below.Implementations within the scope of the present disclosure may alsoinclude physical and other computer-readable media for carrying orstoring computer-executable instructions and/or data structures. Suchcomputer-readable media can be any available media that can be accessedby a general purpose or special purpose computer system.Computer-readable media that store computer-executable instructions arecomputer storage media (devices). Computer-readable media that carrycomputer-executable instructions are transmission media. Thus, by way ofexample, and not limitation, implementations of the disclosure cancomprise at least two distinctly different kinds of computer-readablemedia: computer storage media (devices) and transmission media.

Computer storage media (devices) includes RAM, ROM, EEPROM, CD-ROM,solid state drives (“SSDs”) (e.g., based on RAM), Flash memory,phase-change memory (“PCM”), other types of memory, other optical diskstorage, magnetic disk storage or other magnetic storage devices, or anyother medium which can be used to store desired program code means inthe form of computer-executable instructions or data structures andwhich can be accessed by a general purpose or special purpose computer.

An implementation of the devices, systems, and methods disclosed hereinmay communicate over a computer network. A “network” is defined as oneor more data links that enable the transport of electronic data betweencomputer systems and/or modules and/or other electronic devices. Wheninformation is transferred or provided over a network or anothercommunications connection (either hardwired, wireless, or a combinationof hardwired or wireless) to a computer, the computer properly views theconnection as a transmission medium. Transmissions media can include anetwork and/or data links which can be used to carry desired programcode means in the form of computer-executable instructions or datastructures and which can be accessed by a general purpose or specialpurpose computer. Combinations of the above should also be includedwithin the scope of computer-readable media.

Computer-executable instructions comprise, for example, instructions anddata which, when executed at a processor, cause a general purposecomputer, special purpose computer, or special purpose processing deviceto perform a certain function or group of functions. The computerexecutable instructions may be, for example, binaries, intermediateformat instructions such as assembly language, or even source code.Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the described features or acts described above.Rather, the described features and acts are disclosed as example formsof implementing the claims.

Those skilled in the art will appreciate that the disclosure may bepracticed in network computing environments with many types of computersystem configurations, including, personal computers, desktop computers,laptop computers, message processors, hand-held devices, multi-processorsystems, microprocessor-based or programmable consumer electronics,network PCs, minicomputers, mainframe computers, mobile telephones,PDAs, tablets, pagers, routers, switches, various storage devices, andthe like. The disclosure may also be practiced in distributed systemenvironments where local and remote computer systems, which are linked(either by hardwired data links, wireless data links, or by acombination of hardwired and wireless data links) through a network,both perform tasks. In a distributed system environment, program modulesmay be located in both local and remote memory storage devices.

Further, where appropriate, functions described herein can be performedin one or more of: hardware, software, firmware, digital components, oranalog components. For example, one or more application specificintegrated circuits (ASICs) can be programmed to carry out one or moreof the systems and procedures described herein. Certain terms are usedthroughout the following description and Claims to refer to particularsystem components. As one skilled in the art will appreciate, componentsmay be referred to by different names. This document does not intend todistinguish between components that differ in name, but not function.

Referring now to the figures, FIG. 1 illustrates a vehicle 100 thatincludes an automated driving/assistance system 102. The automateddriving/assistance system 102 may be used to automate or controloperation of the vehicle 100. For example, the automateddriving/assistance system 102 may control one or more of braking,steering, acceleration, lights, alerts, driver notifications, radio, orany other auxiliary systems of the vehicle 100. The automateddriving/assistance system 102 may include a plurality of systems anddevices including actuators, such as electric motors, to controlbraking, steering or the like. The automated driving/assistance system102 includes a localization component 104, which is used to determine alocation of the vehicle 100 based on any data or sensors that areavailable at the time. The vehicle 100 also includes one or more radarsystems 106, one or more LIDAR systems 108, one or more camera systems110, a GPS 112, a data store 114, and a transceiver 116. It will beappreciated that the embodiment of FIG. 1 is given by way of exampleonly. Other embodiments may include fewer or additional componentswithout departing from the scope of the disclosure. Additionally,illustrated components may be combined or included within othercomponents without limitation. For example, the localization component104 may be separate from the automated driving/assistance system 102 andthe data store 114 may be included as part of the automateddriving/assistance system 102 and/or part of the localization system104.

A radar system 106 may include any radar system well known in the art.Radar system operations and performance is generally well understood. Ingeneral, a radar system 106 operates by transmitting radio signals anddetecting reflections off objects. In ground applications, the radar maybe used to detect physical objects, such as other vehicles, landscapes(such as trees, cliffs, rocks, hills, or the like), road edges, signs,buildings, or other objects. The radar system 106 may use the reflectedradio waves to determine a size, shape, distance, surface texture, orother information about a physical object or material. For example, theradar system 106 may sweep an area to obtain data or objects within aspecific range and viewing angle of the radar system 106. In oneembodiment, the radar system 106 is configured to generate perceptioninformation from a region near the vehicle, such as one or more regionsnearby or surrounding the vehicle 100. For example, the radar system 106may obtain data about regions of the ground or vertical area immediatelyneighboring or near the vehicle 100. The radar system 106 may includeone of many widely available commercially available radar systems. Inone embodiment, the radar system 106 may provide perception dataincluding a two dimensional or three-dimensional map or model to theautomated driving/assistance system 102 for reference or processing. Aswill be appreciated by one skilled in the art in light of the presentdisclosure, some radar systems 106, which are commercially available,can operate in some of the most severe and adverse weather conditionswith little or no degradation in the quality or accuracy of perceptiondata. For example, wet surfaces, snow, and fog may have very littleimpact on an ability of the radar system 106 to accurately locate anddetect ranges to objects.

A LIDAR system 108 may include any LIDAR system well known in the art.Principles of operation and performance of LIDAR systems are generallywell understood. In general, the LIDAR system 108 operates by emittingvisible wavelength or infrared wavelength lasers and detectingreflections of the light off objects. In ground applications, the lasersmay be used to detect physical objects, such as other vehicles,landscapes (such as trees, cliffs, rocks, hills, or the like), roadedges, signs, buildings, or other objects. The LIDAR system 108 may usethe reflected laser light to determine a size, shape, distance, surfacetexture, or other information about a physical object or material. Forexample, the LIDAR system 108 may sweep an area to obtain data orobjects within a specific range and viewing angle of the LIDAR system108. For example, the LIDAR system 108 may obtain data about regions ofthe ground or vertical area immediately neighboring or near the vehicle100. The LIDAR system 108 may include one of many widely availablecommercially available LIDAR systems. In one embodiment, the LIDARsystem 108 may provide perception data including a two dimensional orthree-dimensional model or map of detect objects or surfaces.

Although LIDAR may be used to obtain highly accurate and highly detailedinformation about surrounding objects and surfaces, the quality of dataobtain by LIDAR systems 108 may degrade significantly in wet situations.For example, many road surfaces will reflect a significant portion oflaser light back toward a LIDAR system 108 when dry. However, if thesurface becomes wet, the laser may be reflected, but may continue totravel away from the LIDAR system 108. Thus, in high rain or puddlingsituations, LIDAR data may degrade significantly and make it extremelydifficult or impossible to accurately determine locations of roads,vehicle, or other vehicles with sufficient certainty. LIDAR system datamay also degrade significantly in high rain or snow situations becausethe laser light may be reflected by snowflakes or rain drops. Thus, thereturned data may have a significant amount of “noise” that may obscureobjects of interest such as vehicles, trees, curbs, the roadway, people,or the like. In these situations, radar may be far superior anddependable.

A camera system 110 may include one or more cameras, such as visiblewavelength cameras or infrared cameras. The camera system 110 mayprovide a video feed or periodic images, which can be processed forobject detection, road identification and positioning, or otherdetection or positioning. In one embodiment, the camera system 110 mayinclude two or more cameras, which may be used to provide ranging (e.g.,detect a distance) for objects within view of the two or more cameras.

Although, cameras can provide very good and detailed data for anautomated driving/assistance system 102, the quality of data can degradesignificantly in the dark or in the presence of certain weather relatedconditions, including fog, rain, or snow. This is especially true forautomated driving/assistance systems 102, which process a video or imagefeed to assist driving as any “noise” or obstruction caused by theweather related conditions, including fog, rain, or snow can make itvery difficult for automated algorithms to identify or detect objects ordetermine distances.

The GPS system 112 is one embodiment of a positioning system that mayprovide a geographical location of the vehicle 100 based on satellite orradio tower signals. GPS systems 112 are well-known and widely availablein the art. Although GPS systems 112 can provide very accuratepositioning information, GPS systems 112 generally provide little or noinformation about distances between the vehicle and other objects.Rather, they simply provide a location, which can then be compared withother data, such as maps, to determine distances to other objects,roads, or locations of interest. Although GPS systems 112 can experiencedegradation due to adverse weather conditions, high quality or accuracyGPS data may still be obtained in some situations where camera data orLIDAR data is unavailable or below a desired quality.

The data store 114 stores map data, a driving history, and other data,which may include other navigational data, settings, or operatinginstructions for the automated driving/assistance system 102. The mapdata may include location data, such as GPS location data, for roads.For example, the location data for roads may include location data forspecific lanes, such as lane direction, merging lanes, highway orfreeway lanes, exit lanes, or any other lane or division of a road. Thelocation data for roads may also include data regarding the edges of theroads, details about lane type (e.g., commuter lane, passing lane),details about lane direction, or any other details. In one embodiment,the map data includes location data about one or more structures orobjects on or near the roads. For example, the map data may include dataregarding GPS sign location, bridge location, building or otherstructure location, or the like. In one embodiment, the map data mayinclude precise location data with accuracy within a few meters orwithin sub meter accuracy. The map data may also include location datafor paths, dirt roads, or other roads or paths, which may be driven by aland vehicle.

The driving history may include location data for past trips taken bythe vehicle 100. For example, the driving history may include GPSlocation data for the previous trips or paths taken. As another example,the driving history may include distance or relative location data withrespect to lane lines, signs, road border lines, or other objects orfeatures on or near the roads. The distance or relative location datamay be determined based on GPS data, radar data, LIDAR data, cameradata, or other sensor data gathered during the previous or past tripstaken by the vehicle 100. This driving history data may be logged by theautomated driving/assistance system 102 for future use if/when sensordata fails. For example, by saving detailed lane location, signlocation, or other data, the automated driving/assistance system 102 maybe able to determine an extremely precise location based on radar dataonly (or a combination of radar and any other availablelocation/navigation data). In one embodiment, the automateddriving/assistance system 102 is configured to log driving data to thedata store 114 for and during any trips or drives taken by the vehicle100.

The transceiver 116 is configured to receive signals from one or moreother data or signal sources. The transceiver 116 may include one ormore radios configured to communicate according to a variety ofcommunication standards and/or using a variety of different frequencies.For example, the transceiver 116 may receive signals from othervehicles, such as vehicle 118. Receiving signals from another vehicle isreference herein as vehicle-to-vehicle (V2V) communication. In oneembodiment, the transceiver 116 may also be used to transmit informationto other vehicles, such as vehicle 118, to potentially assist them inlocating the vehicle 100, other vehicles or objects. During V2Vcommunication the transceiver 116 may receive information from othervehicles about their locations, other traffic, accidents, roadconditions, or any other details that may assist the vehicle 100 and/orautomated driving/assistance system 102 in driving accurately or safely.

The transceiver 116 may receive signals from other signal sources thatare at fixed locations. Infrastructure transceiver 120 may be located ata specific geographic location and may transmit its specific geographiclocation with a time stamp. Thus, the automated driving/assistancesystem 102 may be able to determine a distance from the infrastructuretransceiver 120 based on the time stamp and then determine its locationbased on the location of the infrastructure transceiver 120. Forexample, the transceiver 116 may receive signals from infrastructuretransceivers 120 that are built into road or transportationinfrastructure. In one embodiment, roads may include transmitters placedalong roads that may be used by the vehicle 100 to obtain preciselocations with respect to the roads or other geographic locations.Similarly, magnets or other location mechanisms may also be placed alongor in the roads, which may be sensed by the transceiver 116 or otherdevices. In one embodiment, the transceiver 116 may receive signals fromradio or cell phone towers. For example, the transceiver 116 may includea radio that is able to receive and process location data on licensedspectrums even if it is not capable of communicating information ordecoding voice or other types of data communications. For example, manymobile networks provide location services, which may be used by theautomated driving/assistance system 102. In one embodiment, receiving orsending location data from devices or towers at fixed locations isreferenced herein as vehicle-to-infrastructure (V2X) communication. Inone embodiment, the term V2X communication may also encompass V2Vcommunication.

In one embodiment, the transceiver 116 may send and receive locationdata via a mobile network or cell connection. For example, thetransceiver 116 may receive updated location data for a specific area asthe vehicle 100 travels along a road way. Similarly, the transceiver 116may receive historical driving data for the vehicle 100 or othervehicles that have driven along a road in that location. For example,the transceiver 116 may receive data that indicates locations of signsor objects which may be detectable using a radar system 106. If thetransceiver 116 is able to receive signals from three or moreinfrastructure transceivers 120, the automated driving/assistance system102 may be able to triangulate its geographic location.

Referring now to FIG. 2, there is illustrated a schematic top viewdiagram of a roadway 200. The roadway 200 includes a plurality of lanes202 marked by lines with vehicles 100 and 118 driving on the roadway200. At an intersection of the roadway 200 are traffic signs 204. Nearor on the roadway are a plurality of infrastructure transmitters ortransceivers 120. The vehicle 100 may be able to determine an accuratelocation on the roadway based on radar detection of the signs 204,transceiver detection of the infrastructure transmitters or transceivers120 and signals transmitted by the vehicle 118, and/or any data storedin the data store 114. Thus, even if inclement weather is affecting dataquality of information transmitted from camera systems 110 or LIDARsystems 108, the automated driving/assistance system 102 may be able toaccurately determine the vehicle's 100 location based on the radarsystem 106 and any other available navigation related data.

FIG. 3 is a block diagram illustrating example components of thelocalization component 104. In the depicted embodiment, the localizationcomponent 104 includes a processor 302, storage 304, a locationcomponent 306, a drive controller 308, a data quality component 310, anda V2X component 312. The components 302-312 are given by way ofillustration only and may not all be included in all embodiments. Infact some embodiments may include only one or any combination of two ormore of the components 302-312.

The processor 302 may include any type of general purpose or specialpurpose processor for executing program code or instructions. Forexample, the processor 302 may be used to execute instructionscorresponding to one or more of the other components 304-312. Thestorage 304 may include a computer readable medium that storesinstructions corresponding to the other components 306-312. For example,the storage 304 may store the other components 306-312 as components ofa computer program. The storage 304 may correspond to the data store 114of FIG. 1. In one embodiment, the storage 304 is configured to storedata, such as map data, program code, driving history, or other data.The map data may include a map of one or more roadways or driving paths.In one embodiment, the map includes information about locations of theobject or structure in relation to the road or the driving path.

The location component 306 is configured to determine a location of acorresponding vehicle (such as the vehicle 100 of FIG. 1) on a map basedon radar perception information and other navigation related data, ifany. In one embodiment, the location component receives the perceptioninformation from a radar system 106 for one or more of a ground surfaceand objects in a region near the vehicle 100. In one embodiment, theother navigation related data comprises location information determinedby a positioning system. In one embodiment, the location component 306determines the location of the vehicle 100 based on the radar perceptioninformation and data from a satellite positioning system. In oneembodiment, the location component 306 determines the location of the ofthe vehicle 100 based on the information from the satellite positioningsystem and based on a location of an object or structure detected by theperception information from the radar system 106, wherein the object orstructure is identified in the map. For example, the map may indicate alocation of the object or structure and the location component 306 maydetermine where the distance from the object or structure intersectswithin an error region of GPS data.

In one embodiment, the other navigation related data includes locationinformation determined based on a V2V communication and/or a V2Xcommunication. For example, the location component 306 may receivelocation or perception information from an infrastructure system, suchas from infrastructure transceiver 120, or another vehicle, such asvehicle 118, and determine the location of the vehicle 100 based on thelocation or perception information from the infrastructure system or theother vehicle. In one embodiment, the other navigation related dataincludes trip data from one or more previous trips taken by the vehicle100. In one embodiment, the location component 304 may determine alocation of the vehicle 100 or another object based on radar data andany combination of LIDAR data, camera image data, V2V data, V2X data,map data, or any other data discussed herein.

In one embodiment, the location component 304 receives the perceptioninformation from the radar system 106, the LIDAR system 108, the camerasystem 110, the GPS 112 or from the infrastructure system, such as frominfrastructure transceiver 120, or another vehicle, such as vehicle 118,or from other sensors. The radar data and data from various sensors maybe combined and/or processed to determine the current location of thevehicle 100 by making use of radar detections, which may be high densityor other radar detections, in localization methods analogous to the useof LIDAR point clouds for localization. The live radar detections may becompared to maps and other data available in the memory of the vehicle100 to determine the current location of the vehicle 100. In oneembodiment, the radar data and data from various sensors may be combinedand/or processed to determine the current location of the vehicle 100 bytracking radar detections over time and comparing those detections toGPS data over time, so that GPS drift can be corrected during the drive.

The drive controller component 308 is to control driving of the vehicle100 based on the map and the determined location. In one embodiment, thedrive controller component 308 may determine a driving maneuver to beperformed by the vehicle 100 and provide control signals to one or moreactuators or systems to control steering, braking, or any other systemof the vehicle 100. In one embodiment, the drive controller component308 may control driving of the vehicle 100 by causing the vehicle 100 toperform a driving maneuver based on the determined location on the map.In one embodiment, the drive controller component 308 may controldriving of the vehicle 100 by providing the position of the vehicle 100to an autonomous driving system, such as automated driving/assistancesystem 102, of the vehicle 100, which may then perform driving maneuversor driving based on the position.

The data quality component 310 is configured to determine that one ormore sensor units are not providing usable data or are damaged. Forexample, the data quality component 310 may determine that the LIDARsystem 108, camera system 110, or other sensor or data input is notproviding usable data. For example, the data quality component 310 maydetermine that a sensor is damaged or may determine that data qualityhas dropped below a threshold. In one embodiment, the data qualitycomponent 310 may determine that LIDAR data or camera data is not usablebased on an amount of noise in the data or based on low light or lowlaser reflection. In one embodiment, the data quality component 310 maydetermine that one or more sensors are not operating based on a signalfrom the one or more sensors explicitly indicating that the sensors arenot functioning. In one embodiment, the data quality component 310 isconfigured to determine that the one or more sensor units are notproviding usable data or are damaged based on one or more of currentweather conditions and determining the one or more sensor units are notproviding any data. In one embodiment, the data quality component 310may receive data via a mobile network or Internet connection thatweather conditions are bad for camera or LIDAR data.

The V2X component 312 is configured to receive V2V or V2Xcommunications. In one embodiment, the V2X component 312 provides theV2V or V2X communications to the location component 306 or the storage304. For example, the location component 306 may determine a location ofa vehicle based on the V2V and/or V2X communications.

Referring now to FIG. 4, there is illustrated a schematic flow chartdiagram of a method 400 for perception and localization for a roadvehicle or for an automated driving or automated assistance system of avehicle. The method 400 may be performed by an automateddriving/assistance system or a localization component, such as theautomated driving/assistance system 102 of FIG. 1 or the localizationcomponent 104 of FIG. 3.

The method 400 begins by storing a map of a road or driving path that avehicle, such as vehicle 100, may travel at 410 in storage 304. It willbe appreciated that the storage 304 may also store information fromprevious routes and trips driven by the vehicle at 412. The localizationcomponent 104 receives perception information from a radar system forone or more of ground and objects in a region near the vehicle at 420.The localization component 104 may also receive location informationfrom a satellite positioning system at 430. The localization component104 may also receive location or perception information from aninfrastructure system or another vehicle at 432. A data qualitycomponent 310 determines that one or more of a camera and a LIDAR systemare not providing usable data or are damaged at 434. A locationcomponent 306 determines a location of an object or structure detectedby the perception information from the radar system, wherein the objector structure is identified in the map at 436. The location component 306determines a location of the vehicle on the map based on the radarperception information and a satellite positioning system at 438. Adrive controller component 308 performs or causes a vehicle to perform adriving maneuver based on the determined location on the map at 440.

EXAMPLES

The following examples pertain to further embodiments.

Example 1 is a vehicle driving system that includes: storage media forstoring a map of roadways; a radar system configured to generateperception information from a region near the vehicle; a locationcomponent configured to determine a location of the vehicle on the mapbased on the radar perception information and other navigation relateddata; and a drive controller configured to control driving of thevehicle based on the map and the determined location.

In Example 2, the vehicle driving system of Example 1 further includesone or more additional sensor units and a data quality componentconfigured to determine that one or more sensor units are not providingusable data or are damaged. The location component is configured todetermine the location of the vehicle based on the radar perceptioninformation in response to determining that the one or more sensor unitsare not providing usable data or are damaged.

In Example 3, the data quality component of Example 2 is configured todetermine that the one or more sensor units are not providing usabledata or are damaged based on one or more of: current weather conditionsor a determination that the one or more sensor units are not providingany data.

In Example 4, the one or more additional sensor units in any of Examples2-3 include one or more of a camera and a LIDAR system, wherein the dataquality component is configured to determine that one or more of thecamera and the LIDAR system are not providing usable data or aredamaged.

In Example 5, the other navigation related data in any of Examples 1˜4includes one or more of location information determined by a positioningsystem, location information determined based on a vehicle-to-vehiclecommunication, location information determined based on avehicle-to-infrastructure communication, and trip data from one or moreprevious trips taken by the vehicle.

Example 6 is a method of perception and localization for a road vehicle.The method includes: storing a map of a road or driving path; receivingperception information from a radar system for one or more of ground andobjects in a region near the vehicle; receiving location informationfrom a satellite positioning system; determining a location of thevehicle on the map based on the radar perception information and thesatellite positioning system; and performing a driving maneuver based onthe determined location on the map.

In Example 7, the method of Example 6 further includes storinginformation from previous routes and trips driven by the vehicle andwherein determining the location further comprises determining thelocation based on the information from previous routes and trips drivenby the vehicle.

In Example 8, determining the location of the of the vehicle on the mapin any of Examples 6-7 includes determining based on the informationfrom the satellite positioning system and based on a location of anobject or structure detected by the perception information from theradar system, wherein the object or structure is identified in the map.

In Example 9, storing the map in any of Examples 6-8 includes storing amap comprising information about locations of the object or structure inrelation to the road or the driving path.

In Example 10, the method of any of Examples 6-9 further includesreceiving location or perception information from an infrastructuresystem or another vehicle, wherein determining the location furtherincludes determining based on the location or perception informationfrom the infrastructure system or the another vehicle.

Example 11 is the method of any of Examples 6-10 wherein: the roadvehicle further comprises one or more of a camera and a LIDAR system;the method further comprises determining that one or more of the cameraand the LIDAR system are not providing usable data or are damaged; anddetermining the location of the vehicle based on the perceptioninformation from a radar system is performed in response to determiningthat the camera or LIDAR system are not providing usable data or aredamaged.

Example 12 is computer readable storage media storing instructions that,when executed by a processor, cause the processor to: obtain map datafrom storage, the map data corresponding to a map of a road; obtainnavigation related data from one or more sources; obtain radar systemdata for a region near a vehicle; process the radar system data and thenavigation related data to locate a position of a vehicle in relation tothe road; and provide the position of the vehicle to an autonomousdriving system of the vehicle.

In Example 13, the navigation related data in Example 12 includes one ormore of: satellite positioning data from a satellite positioning system;information received via a vehicle-to-vehicle communication; informationreceived via a vehicle-to-infrastructure communication; and informationfrom previous routes and trips driven by the vehicle.

In Example 14, the map data in any of Examples 12-13 includesinformation about locations of an object or structure in relation to theroad.

In Example 15, the radar system data in any of Examples 12-14 includesinformation about a location of the object or structure in relation tothe vehicle, and wherein processing the radar system data to locate theposition comprises determining the location based on the locations ofthe object or structure according to the map.

In Example 16, the vehicle in any of Examples 12-15 includes one or moreof a camera and a LIDAR system and wherein the instructions furthercause the processor to determine that one or more of the camera and theLIDAR system are not providing usable data or are damaged.

In Example 17, the instructions in any of Examples 12-16 cause theprocessor to process the radar system data and the navigation relateddata to locate the position in response to determining that the cameraor LIDAR system are not providing usable data or are damaged.

It should be noted that the sensor embodiments discussed above maycomprise computer hardware, software, firmware, or any combinationthereof to perform at least a portion of their functions. For example, asensor may include computer code configured to be executed in one ormore processors, and may include hardware logic/electrical circuitrycontrolled by the computer code. These example devices are providedherein purposes of illustration, and are not intended to be limiting.Embodiments of the present disclosure may be implemented in furthertypes of devices, as would be known to persons skilled in the relevantart(s).

Embodiments of the disclosure have been directed to computer programproducts comprising such logic (e.g., in the form of software) stored onany computer useable medium. Such software, when executed in one or moredata processing devices, causes a device to operate as described herein.

While various embodiments of the present disclosure have been describedabove, it should be understood that they have been presented by way ofexample only, and not limitation. It will be apparent to persons skilledin the relevant art that various changes in form and detail can be madetherein without departing from the spirit and scope of the disclosure.Thus, the breadth and scope of the present disclosure should not belimited by any of the above-described exemplary embodiments, but shouldbe defined only in accordance with the following claims and theirequivalents. The foregoing description has been presented for thepurposes of illustration and description. It is not intended to beexhaustive or to limit the disclosure to the precise form disclosed.Many modifications and variations are possible in light of the aboveteaching. Further, it should be noted that any or all of theaforementioned alternate implementations may be used in any combinationdesired to form additional hybrid implementations of the disclosure.

Further, although specific implementations of the disclosure have beendescribed and illustrated, the disclosure is not to be limited to thespecific forms or arrangements of parts so described and illustrated.The scope of the disclosure is to be defined by the claims appendedhereto, any future claims submitted here and in different applications,and their equivalents.

What is claimed is:
 1. A method comprising: identifying drive historydata comprising route geometry for a route driven by a vehicle;receiving sensor data from one or more sensors of the vehicle; receivingsupplemental data comprising one or more of a vehicle-to-vehiclecommunication or a vehicle-to-infrastructure communication; merging thedrive history data with the sensor data and the supplemental data togenerate merged data; identifying a location of the vehicle based on themerged data.
 2. The method of claim 1, wherein identifying the locationof the vehicle comprises identifying the location of the vehicle on aroadway based on radar detection of signs near the roadway andtransceiver detection of infrastructure transceivers providing a signalto the vehicle.
 3. The method of claim 1, wherein the sensor datacomprises radar perception data comprising one or more of: a location ofa ground surface near the vehicle; or a location of an object near thevehicle.
 4. The method of claim 1, wherein the supplemental datacomprises a location of a transceiver providing the vehicle-to-vehiclecommunication or the vehicle-to-infrastructure communication.
 5. Themethod of claim 1, further comprising determining a LIDAR system is notproviding usable data or is damaged based on one or more of: currentweather conditions; or determining the LIDAR system is not providing anydata.
 6. The method of claim 5, further comprising: in response todetermining the LIDAR system is not providing usable data or is damaged,localizing the vehicle relative to the drive history data based on thesupplemental data and sensor data received from one or more vehiclesensors not comprising the LIDAR system; and localizing the vehiclerelative to the drive history data based on data from the LIDAR systemwhen the LIDAR system is providing usable data.
 7. The method of claim1, further comprising controlling driving of the vehicle based on thedrive history data and the determined location of the vehicle relativeto the drive history data.
 8. The method of claim 1, wherein identifyingthe location of the vehicle comprises localizing the vehicle relative tothe drive history data by localizing the vehicle on a map comprising theroute geometry.
 9. The method of claim 1, wherein receiving thesupplemental data comprises wirelessly receiving the vehicle-to-vehiclecommunication from one or more other vehicles and wirelessly receivingthe vehicle-to-infrastructure communication from one or moreinfrastructure transceivers built into a road or transportationinfrastructure.
 10. The method of claim 1, wherein the drive historydata comprises a high definition map comprising location information forroads, lane markings, and traffic signs in terms of global positioningsystem (GPS) coordinates, and further comprises behavioral features fromprevious trips travelled by the vehicle.
 11. A system comprising one ormore processors for executing instructions stored in non-transitorycomputer readable storage media, the instructions comprising:identifying drive history data comprising route geometry for a routedriven by a vehicle; receiving sensor data from one or more sensors ofthe vehicle; receiving supplemental data comprising one or more of avehicle-to-vehicle communication or a vehicle-to-infrastructurecommunication; merging the drive history data with the sensor data andthe supplemental data to generate merged data; identifying a location ofthe vehicle based on the merged data.
 12. The system of claim 11,wherein the instructions are such that identifying the location of thevehicle comprises identifying the location of the vehicle on a roadwaybased on radar detection of signs near the roadway and transceiverdetection of infrastructure transceivers providing a signal to thevehicle.
 13. The system of claim 11, wherein the sensor data comprisesradar perception data comprising one or more of: a location of a groundsurface near the vehicle; or a location of an object near the vehicle.14. The system of claim 11, wherein the supplemental data comprises alocation of a transceiver providing the vehicle-to-vehicle communicationor the vehicle-to-infrastructure communication.
 15. The system of claim11, wherein the instructions further comprise controlling driving of thevehicle based on the drive history data and the determined location ofthe vehicle relative to the drive history data.
 16. Non-transitorycomputer readable storage media for storing instructions to be executedby one or more processors, the instructions comprising: identifyingdrive history data comprising route geometry for a route driven by avehicle; receiving sensor data from one or more sensors of the vehicle;receiving supplemental data comprising one or more of avehicle-to-vehicle communication or a vehicle-to-infrastructurecommunication; merging the drive history data with the sensor data andthe supplemental data to generate merged data; identifying a location ofthe vehicle based on the merged data.
 17. The non-transitory computerreadable storage media of claim 16, wherein the instructions furthercomprise determining a LIDAR system is not providing usable data or isdamaged based on one or more of: current weather conditions; ordetermining the LIDAR system is not providing any data.
 18. Thenon-transitory computer readable storage media of claim 17, wherein theinstructions further comprise: in response to determining the LIDARsystem is not providing usable data or is damaged, localizing thevehicle relative to the drive history data based on the supplementaldata and sensor data received from one or more vehicle sensors notcomprising the LIDAR system; and localizing the vehicle relative to thedrive history data based on data from the LIDAR system when the LIDARsystem is providing usable data.
 19. The non-transitory computerreadable storage media of claim 16, wherein the instructions are suchthat identifying the location of the vehicle comprises localizing thevehicle relative to the drive history data by localizing the vehicle ona map comprising the route geometry.
 20. The non-transitory computerreadable storage media of claim 16, wherein the instructions are suchthat receiving the supplemental data comprises wirelessly receiving thevehicle-to-vehicle communication from one or more other vehicles andwirelessly receiving the vehicle-to-infrastructure communication fromone or more infrastructure transceivers built into a road ortransportation infrastructure.